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Insurance Claims Agent

Cortex Analyst
Marie Duran, Constantin Stanca, Cameron Shimmin
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Overview

This solution delivers an AI-powered insurance claims processing platform that transforms how claims teams handle and analyze claims data. By integrating Snowflake Cortex services, it processes both structured and unstructured information, enabling users to gain comprehensive insights through natural language queries.

The solution demonstrates how insurance organizations can modernize their claims operations by centralizing claims data, supporting documents, audio files, and AI capabilities on a unified platform—providing a complete view of each claim while ensuring compliance with state guidelines.

Key Features

  • Intelligent Claims Analysis: Leverage Snowflake Cortex Analyst with Semantic Views, Cortex Search, AISQL, and Agents for sophisticated data analysis and query generation. The system interprets complex questions about claims, payments, reserves, and compliance, delivering instant, data-driven answers.
  • Conversational Claims Interface: Snowflake Intelligence serves as the UI, enabling users to ask complex questions about claims using natural language. Query payment timelines, reserve rationales, authority compliance, and settlement status without writing SQL.
  • Multimodal Evidence Analysis: Describe and compare claims images with claim descriptions to verify if supporting evidence aligns with the reported incident. This powerful capability helps detect inconsistencies and validate claim authenticity.
  • Audio Transcription: Transcribe text from audio or video files with optional timestamps and speaker labels. Analyze call recordings for tone, sentiment, and key information to support claims decisions.
  • Unified Data Integration: Join unstructured and structured data to provide a complete view of each claim, combining claims records, financial transactions, and authorization data with claim file notes, state guidelines, invoices, photo evidence, and audio files.

How It Works

This solution leverages Snowflake's native AI capabilities to create a seamless, end-to-end claims processing platform without external infrastructure.

  • Data Foundation: Claims records, financial transactions, payment data, reserve information, and authorization records are stored as structured data in Snowflake tables. Supporting documents including claim file notes, state insurance guidelines, invoices, claim photo evidence, and audio call files are uploaded to Snowflake stages.
  • Cortex Search Services: Specialized search services are configured to vectorize and enable semantic search across different document types: claim file notes, state insurance guidelines, and parsed documents. This allows the system to understand the meaning and context of user queries.
  • Cortex Analyst: A semantic model defines the relationships, metrics, and business logic within the claims data, enabling natural language queries about payments, reserves, authority levels, and compliance timelines.
  • Multimodal Processing: Image analysis capabilities compare uploaded claim photos against reported incident descriptions to verify evidence alignment. Audio transcription converts call recordings into searchable text for comprehensive claim analysis.
  • Snowflake Intelligence: An AI agent is created and equipped with both the Cortex Analyst semantic model and Cortex Search services. Custom orchestration instructions enable the agent to intelligently route queries, combining structured analytics with unstructured document insights to provide comprehensive answers.

Business Impact

This solution helps insurance organizations transition from fragmented, manual claims processes to an integrated, AI-driven experience, resulting in:

  • Faster, More Accurate Decisions: Claims adjusters and examiners can instantly synthesize information from all sources—structured data, notes, images, and guidelines—enabling faster, data-driven assessments with built-in evidence verification.
  • Operational Efficiency and Consistency: Reduces claim cycle time, ensures consistent application of company and state guidelines, and enables teams to handle higher claim volumes without proportional staff increases.
  • Advanced Fraud Detection: The system's ability to join structured data with unstructured files (like call transcripts for tone analysis) and compare image evidence against claim descriptions provides powerful tools for flagging suspicious or inconsistent claims.
  • Enhanced Compliance and Auditability: By combining structured data with parsed state guidelines, the system helps ensure claims decisions are compliant with regulations, providing a clear, auditable trail for every decision.
  • Cost Reduction and Improved Customer Experience: Automating document ingestion and accelerating the decision process directly reduces operational costs and leads to faster, more positive interactions for policyholders.

Use Cases and Applications

This solution serves as a comprehensive foundation for various insurance claims processing applications:

  • Payment Processing Analysis: Analyze what percentage of payments were issued to vendors within specific timeframes after invoice receipt (3–5 days, 8–13 days, 14–29 days, or 30+ days), identifying bottlenecks and improving payment efficiency.
  • Reserve Management: Verify whether reserve rationales are documented in claim file notes, assess if rationales adequately explain reserve figures, and confirm reserve extensions were requested in a timely manner.
  • Authority Compliance Monitoring: Identify when payments were issued in excess of current reserve amounts on open claims, flag reserving or payment amounts exceeding examiner authority, and ensure all elements of authority are properly handled.
  • State Guidelines Compliance: Verify payments are made according to state guidelines and confirm claims are settled within required timelines, reducing compliance risk and regulatory exposure.
  • Evidence Verification: Generate AI-driven summaries of claim images, extract and validate invoice data against payments made, and confirm that submitted images align with the reported claim details.
  • Fraud Investigation Support: Enable Special Investigations Units to leverage multimodal analysis for detecting inconsistencies between claim descriptions, supporting evidence, and transaction patterns.
  • Claims Audit Preparation: Provide comprehensive documentation and analysis trails for internal audits and regulatory reviews, demonstrating consistent application of guidelines and procedures.

Get Started

Ready to transform your claims operations with AI-powered insights? This solution includes everything you need to get up and running quickly.

Run the Demo on GitHub →

The repository contains complete setup scripts, sample claims data, semantic model definitions, and step-by-step instructions for configuring Snowflake Intelligence with Cortex Analyst and Cortex Search services.

Setup Instructions

Follow these steps to set up the environment and run the demo.

Step 1: Initialize Database Objects

  1. Log into Snowflake and open a new SQL worksheet.
  2. Import and run scripts/setup.sql. This script creates the necessary database objects:
    • Database: INSURANCE_CLAIMS_DEMO
    • Schema: LOSS_CLAIMS
    • Stage: LOSS_EVIDENCE
    • Tables:
      • Claims
      • Claim Lines
      • Financial Transactions
      • Authorization
      • Parsed_invoices
      • Parsed_guidelines
      • Parsed_claim_notes
      • GUIDELINES_CHUNK_TABLE
      • NOTES_CHUNK_TABLE

Step 2: Upload Evidence Files

  1. Upload all files in the files directory to the LOSS_EVIDENCE stage in INSURANCE_CLAIMS_DEMO.LOSS_CLAIMS.

Step 3: Configure Cortex AI

  1. Import and run scripts/setup_cortex_ai.sql. This script sets up the Cortex AI components including the semantic view and agent configuration.

Step 4: Start Using the Agent

  1. Navigate to Snowflake Intelligence and start asking questions!

Sample Questions

This demo helps answer questions like:

  1. Payment Processing Time: What percentage of payments were issued to the vendor within the following timeframes after invoice receipt?

    • 3–5 calendar days
    • 8–13 calendar days
    • 14–29 calendar days
    • 30+ calendar days

  2. Reserve Rationale Presence: Was a reserve rationale documented in the claim file notes?

  3. Reserve Rationale Sufficiency: Did the reserve rationale adequately explain the reserve figure(s) set?

  4. Reserve Extension Timeliness: Was the reserve extension requested in a timely manner?

  5. Payment Over Reserve: Was a payment issued in excess of the current reserve amount on an open claim?

  6. Authority Violation (Reserves/Payments): Were the reserving or payment amounts in excess of the examiner's authority?

  7. Authority Compliance: When the claim exceeded the examiner's authority, were all elements of authority properly handled?

  8. Payment Compliance: Was the payment made according to the state guidelines?

  9. Settlement Timeliness: According to the state guidelines, was the claim settled within the required timelines?

  10. AI-Driven Image Summary: Generate an AI-driven summary of the image.

  11. Invoice Validation: Extract invoice data and validate with the payments made.

  12. Image Alignment Verification: Confirm that the images shown align with the claim made.

Updated 2025-12-19

This content is provided as is, and is not maintained on an ongoing basis. It may be out of date with current Snowflake instances